Shu Qian, Napelenok Sergey L, Hutzell William T, Baker Kirk R, Henderson Barron H, Murphy Benjamin N, Hogrefe Christian
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Geosci Model Dev. 2023 Apr 28;16(8):2303-2322. doi: 10.5194/gmd-16-2303-2023.
The Integrated Source Apportionment Method (ISAM) has been revised in the Community Multiscale Air Quality (CMAQ) model. This work updates ISAM to maximize its flexibility, particularly for ozone (O) modeling, by providing multiple attribution options, including products inheriting attribution fully from nitrogen oxide reactants, fully from volatile organic compound (VOC) reactants, equally from all reactants, or dynamically from NO or VOC reactants based on the indicator gross production ratio of hydrogen peroxide (HO) to nitric acid (HNO). The updated ISAM has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3.2 and beyond). This study's primary objective is to document these ISAM updates and demonstrate their impacts on source apportionment results for O and its precursors. Additionally, the ISAM results are compared with the Ozone Source Apportionment Technology (OSAT) in the Comprehensive Air-quality Model with Extensions (CAMx) and the brute-force method (BF). All comparisons are performed for a 4 km horizontal grid resolution application over the northeastern US for a selected 2 d summer case study (9 and 10 August 2018). General similarities among ISAM, OSAT, and BF results add credibility to the new ISAM algorithms. However, some discrepancies in magnitude or relative proportions among tracked sources illustrate the distinct features of each approach, while others may be related to differences in model formulation of chemical and physical processes. Despite these differences, OSAT and ISAM still provide useful apportionment data by identifying the geographical and temporal contributions of O and its precursors. Both OSAT and ISAM attribute the majority of O and NO contributions to boundary, mobile, and biogenic sources, whereas the top three contributors to VOCs are found to be biogenic, boundary, and area sources.
综合源解析方法（ISAM）已在社区多尺度空气质量（CMAQ）模型中进行了修订。这项工作对ISAM进行了更新，通过提供多种归因选项，特别是在臭氧（O₃）建模方面，以最大限度地提高其灵活性，这些选项包括完全从氮氧化物反应物继承归因的产物、完全从挥发性有机化合物（VOC）反应物继承归因的产物、从所有反应物均等继承归因的产物，或基于过氧化氢（HO₂）与硝酸（HNO₃）的指示性总生成比从NOₓ或VOC反应物动态继承归因的产物。更新后的ISAM已被纳入CMAQ最新的可公开获取版本（v5.3.2及更高版本）。本研究的主要目的是记录这些ISAM更新内容，并展示它们对O₃及其前体的源解析结果的影响。此外，将ISAM的结果与扩展综合空气质量模型（CAMx）中的臭氧源解析技术（OSAT）和蛮力法（BF）进行了比较。所有比较均针对美国东北部4公里水平网格分辨率应用，选取了2018年8月9日和10日这一夏季案例进行研究。ISAM、OSAT和BF结果之间的总体相似性为新的ISAM算法增添了可信度。然而，所追踪源之间在量级或相对比例上的一些差异说明了每种方法的独特特征，而其他差异可能与化学和物理过程的模型公式差异有关。尽管存在这些差异，但OSAT和ISAM通过识别O₃及其前体的地理和时间贡献，仍然提供了有用的解析数据。OSAT和ISAM都将大部分O₃和NOₓ贡献归因于边界源、移动源和生物源，而VOCs的前三大贡献源则是生物源、边界源和区域源。
